GLImER: A New Global Database of Teleseismic Receiver Functions for Imaging Earth Structure

Rondenay, S.; Spieker, Kathrin; Sawade, Lucas; Halpaap, Felix; Farestveit, Mari

doi:10.1785/0220160111

Cited by 15 publications

(17 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As in most standard P-wave RF studies (see, e.g. Rondenay et al 2017), we restricted our dataset to high signal-to-noise ratio signals from teleseismic earthquakes of magnitude M w ≥ 5.5 that occurred at 30…”

Section: Datamentioning

confidence: 99%

Constraints on the structure of the crust and lithosphere beneath the Azores Islands from teleseismic receiver functions

Spieker

Rondenay

Ramalho

et al. 2018

Geophysical Journal International

Self Cite

View full text Add to dashboard Cite

Section: Datamentioning

confidence: 99%

Constraints on the structure of the crust and lithosphere beneath the Azores Islands from teleseismic receiver functions

Spieker

Rondenay

Ramalho

et al. 2018

Geophysical Journal International

Self Cite

View full text Add to dashboard Cite

“…To better constrain the depth variations of the LAB, we performed (a) an inversion with an imposed discontinuity, (b) a prejudiced inversion, and (c) forward models based on the final smooth model. Seismic phase conversions of S ‐to‐P (

S_{P})

and P ‐to‐S (

P_{S}

) analysis for data sets acquired beneath eastern North America, suggest the presence of a sharp seismic velocity discontinuity located at ∼85–111 km depth, which is attributed to the LAB [ Rychert et al ., ; Abt et al ., ; Rondenay et al ., ].…”

Section: Resultsmentioning

confidence: 99%

“…(c) P

_{S}

RF profile, as produced from the data recorded by the M66A teleseismic receiver, situated in the Nantucket Island, ∼35 km from w14 MT station (Figure 1a). The RF data is taken from the GLImER database [ Rondenay et al ., ].…”

Section: Discussionmentioning

confidence: 99%

“…The map insert shows the survey region along the east coast of the United States. The star in Nantucket Island denotes the position of a teleseismic receiver (M66A) that is used for receiver function analysis [Rondenay et al, 2017]. (b) Key geological features at the vicinity of the study area, marked by a green square (map modified from Crough [1981], Withjack et al [1998], and Eaton and Frederiksen [2007]).…”

Section: Geologic Settingmentioning

confidence: 99%

“…An analysis of P-to-S receiver function (RF) data [Rondenay et al, 2017] from a seismic station located 35 km from the nearest MT station (Figure 1a) exhibits a strong negative P S phase at 109 km depth. This phase is indicative of the LAB, and is comparable to nearby LAB depths determined by Rychert et al [2005Rychert et al [ , 2007 (87-105 km) and Abt et al [2010] (111 6 7 km).…”

Section: Shear-wave Velocity and P S Receiver Functionmentioning

confidence: 99%

See 2 more Smart Citations

Conductivity structure of the lithosphere‐asthenosphere boundary beneath the eastern North American margin

Attias

Evans

Naif

et al. 2017

Geochem Geophys Geosyst

View full text Add to dashboard Cite

Tectonic plate motion and mantle dynamics processes are heavily influenced by the characteristics of the lithosphere-asthenosphere boundary (LAB), yet this boundary remains enigmatic regarding its properties and geometry. The processes involved in rifting at passive margins result in substantial alteration of the lithosphere through the transition from continental to oceanic lithologies. Here we employ marine magnetotelluric (MT) data acquired along a 135 km long profile, offshore Martha's Vineyard, New England, USA, to image the electrical conductivity structure beneath the New England continental margin for the first time. We invert the data using two different MT 2-D inversion algorithms and present a series of models that are obtained using three different parameterizations: fully unconstrained, unconstrained with an imposed LAB discontinuity and a priori constrained lithosphere resistivity. This suite of models infers variability in the depth of the LAB, with an average depth of 115 km at the eastern North America passive margin. Models robustly detect a 350 Xm lithospheric anomalous conductivity zone (LACZ) that extends vertically through the entire lithosphere. Our preferred conductivity model is consistent with regional P-to-S receiver function data, shear-wave velocity, gravity anomalies, and prominent geological features. We propose that the LACZ is indicative of paleolithospheric thinning, either resulting from kimberlite intrusions associated with rifting and the New England Great Meteor hot spot track, or from shear-driven localized deformation related to rifting.

show abstract

Segmentation of Common Conversion Point Stacks using a Neural Network

Sawade

Makus

Irving

et al. 2022

Preprint

View full text Add to dashboard Cite

Receiver functions, an important tool in understanding sub-surface interfaces, can be analysed through carefully implemented neural networks. We demonstrate this approach. Previously, we introduced our receiver function tool set, Pythonic Global Lithospheric Imaging using Earthquake Recordings (PyGLImER). PyGLImER enables us to: [1] create a database of teleseismic event displacement records at worldwide seismic stations, [2] compute receiver functions from these records, and [3] compute volumetric common conversion point (CCP) stacks from the receiver functions and their conversion points. CCP stacking is a standard tool to image the subsurface using receiver functions. The CCP stacks represent rich but large, three-dimensional volumes of data that contain information about discontinuities in Earth's crust and upper mantle. One goal of the interpretation of CCPs is the identification of such discontinuities. Automated picking routines reduce discontinuities to singular peaks and troughs, thus discarding the wealth of information available over the whole depth range, such as integrated discontinuity impedance and regional geometry. However, the obvious alternative, manual picking, is not feasible for large data volumes. Here, we explore the possibility of fully-automated segmentation of 3D CCP volumes through the application of image processing routines and machine learning to successive volume cross-sections. With our picking tool, we manually label discontinuities in CCP slices to serve as training and validation sets.We use these labeled datasets as input to train a convolutional neural network (CNN) to perform pixel-wise identifications in subsurface images. When applied to all slices of the CCP stack, the CNN outputs a fully-segmented 3D model, which furnishes quantitative exploration of subsurface discontinuity morphology. Specifically, we can investigate the thickness/width, intensity, and topography of discontinuities across continents. This information has the potential to improve our understanding of, e.g., mantle transition zone phase transitions and, therefore, mantle dynamics.

show abstract

GLImER: A New Global Database of Teleseismic Receiver Functions for Imaging Earth Structure

Cited by 15 publications

References 23 publications

Constraints on the structure of the crust and lithosphere beneath the Azores Islands from teleseismic receiver functions

Constraints on the structure of the crust and lithosphere beneath the Azores Islands from teleseismic receiver functions

Conductivity structure of the lithosphere‐asthenosphere boundary beneath the eastern North American margin

Segmentation of Common Conversion Point Stacks using a Neural Network

Contact Info

Product

Resources

About